National and Subnational estimates for the United States of America

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally in the United States of America. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Table of Contents


Using data available up to the: 2020-04-19

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by region


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-08) in the United States of America, stratified by state, can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Regions with fewer than 40 confirmed cases reported on a single day are not included in the analysis (light grey).

National summary

Summary (estimates as of the 2020-04-08)

Table 1: Latest estimates (as of the 2020-04-08) of the number of confirmed cases by date of infection, the expected change in daily confirmed cases, the effective reproduction number, the doubling time, and the adjusted R-squared of the exponential fit. The mean and 90% credible interval is shown for each numeric estimate.
Estimate
New confirmed cases by infection date 29523 (29002 – 30010)
Expected change in daily cases Likely decreasing
Effective reproduction no. 1 (1 – 1)
Doubling time (days) -76 (Inf – Inf)
Adjusted R-squared 0.52 (0.29 – 0.78)

Reported confirmed cases, their estimated date of infection, and time-varying reproduction number estimates


Figure 2: A.) Confirmed cases by date of report (bars) and their estimated date of infection. B.) Time-varying estimate of the effective reproduction number. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Estimates are shown until the 2020-04-08.Dark grey ribbon = 50% credible interval. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Time-varying rate of growth and doubling time


Figure 3: A.) Time-varying estimate of the rate of growth, B.) Time-varying estimate of the doubling time in days (note that when the rate of growth is negative the doubling time is assumed to be infinite), C.) The adjusted R-squared estimates indicating the goodness of fit of the exponential regression model (with values closer to 1 indicating a better fit). Estimates are shown until the 2020-04-08. Light ribbon = 90% credible interval; dark ribbon = the 50% credible interval. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Regional Breakdown

Data availability

Limitations

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 4: Confirmed cases with date of infection on the 2020-04-08 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 5: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-08. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 6: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-08. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Reproduction numbers over time in all regions


Figure 7: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-08. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported confirmed cases and their estimated date of infection in all regions

Figure 8: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-08. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Latest estimates (as of the 2020-04-08)

Table 2: Latest estimates (as of the 2020-04-08) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time in each region. The mean and 90% credible interval is shown.
State New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling time (days)
Alabama 197 (156 – 236) Likely decreasing 0.9 (0.8 – 1) -23 (120 – Inf)
Arizona 202 (156 – 239) Unsure 1 (0.9 – 1.2) 82 (15 – Inf)
Arkansas 73 (47 – 100) Unsure 1.1 (0.8 – 1.4) 56 (9.3 – Inf)
California 1234 (1134 – 1332) Likely increasing 1 (1 – 1.1) 180 (35 – Inf)
Colorado 349 (290 – 400) Unsure 1 (0.9 – 1.1) -310 (27 – Inf)
Connecticut 915 (837 – 1009) Unsure 1 (1 – 1.1) 780 (38 – Inf)
Delaware 140 (104 – 172) Unsure 1.1 (0.9 – 1.2) 260 (15 – Inf)
District of Columbia 128 (93 – 160) Unsure 1 (0.8 – 1.2) -250 (16 – Inf)
Florida 964 (881 – 1056) Likely decreasing 1 (0.9 – 1) -60 (140 – Inf)
Georgia 902 (805 – 979) Increasing 1.2 (1.1 – 1.3) 59 (16 – Inf)
Guam 25 (7 – 40) Decreasing 0.6 (0.3 – 0.8) -4.1 (Inf – Inf)
Idaho 32 (14 – 49) Unsure 0.8 (0.5 – 1.2) -12 (16 – Inf)
Illinois 1371 (1254 – 1477) Unsure 1 (0.9 – 1.1) -450 (56 – Inf)
Indiana 471 (406 – 535) Unsure 1 (0.9 – 1.1) -190 (34 – Inf)
Iowa 152 (117 – 188) Increasing 1.2 (1 – 1.4) 20 (8.9 – Inf)
Kansas 85 (61 – 111) Unsure 1.1 (0.8 – 1.3) 730 (11 – Inf)
Kentucky 115 (84 – 145) Unsure 0.9 (0.8 – 1.1) -27 (34 – Inf)
Louisiana 514 (443 – 577) Decreasing 0.7 (0.6 – 0.8) -8.6 (Inf – Inf)
Maine 40 (17 – 58) Likely increasing 1.2 (0.8 – 1.7) 15 (5 – Inf)
Maryland 668 (596 – 743) Unsure 1 (0.9 – 1.1) -74 (63 – Inf)
Massachusetts 1859 (1739 – 1997) Unsure 1 (0.9 – 1.1) -550 (59 – Inf)
Michigan 1097 (985 – 1189) Likely decreasing 1 (0.9 – 1) -44 (290 – Inf)
Minnesota 102 (70 – 129) Unsure 1.1 (0.8 – 1.3) 85 (11 – Inf)
Mississippi 212 (171 – 255) Likely increasing 1.1 (0.9 – 1.3) 36 (12 – Inf)
Missouri 221 (173 – 260) Unsure 1 (0.8 – 1.1) -49 (32 – Inf)
Nebraska 85 (60 – 114) Likely increasing 1.2 (1 – 1.5) 19 (7.3 – Inf)
Nevada 128 (93 – 161) Unsure 0.9 (0.8 – 1.1) -40 (25 – Inf)
New Hampshire 66 (40 – 89) Likely increasing 1.2 (0.9 – 1.5) 18 (6.4 – Inf)
New Jersey 3373 (3198 – 3521) Unsure 1 (0.9 – 1) -300 (110 – Inf)
New Mexico 95 (64 – 122) Unsure 1.1 (0.8 – 1.3) -3000 (13 – Inf)
New York 8499 (8245 – 8780) Decreasing 0.9 (0.9 – 1) -45 (Inf – Inf)
North Carolina 271 (223 – 315) Unsure 1 (0.9 – 1.1) -910 (23 – Inf)
North Dakota 30 (13 – 45) Likely increasing 1.4 (0.9 – 2) 9 (3.7 – Inf)
Ohio 523 (459 – 598) Increasing 1.2 (1.1 – 1.4) 17 (11 – 43)
Oklahoma 99 (68 – 125) Unsure 1 (0.8 – 1.2) -82 (16 – Inf)
Oregon 54 (27 – 74) Unsure 0.9 (0.6 – 1.2) -28 (15 – Inf)
Pennsylvania 1446 (1341 – 1553) Likely decreasing 1 (0.9 – 1) -37 (Inf – Inf)
Puerto Rico 45 (21 – 65) Unsure 0.9 (0.6 – 1.2) -21 (14 – Inf)
Rhode Island 303 (247 – 347) Likely increasing 1.1 (0.9 – 1.3) 48 (16 – Inf)
South Carolina 161 (128 – 202) Unsure 0.9 (0.8 – 1.1) -33 (34 – Inf)
South Dakota 138 (105 – 173) Increasing 1.4 (1.1 – 1.6) 11 (6.3 – 53)
Tennessee 252 (209 – 299) Unsure 1 (0.9 – 1.2) 180 (19 – Inf)
Texas 892 (805 – 974) Unsure 1 (0.9 – 1.1) -53 (89 – Inf)
Utah 111 (76 – 137) Unsure 1 (0.8 – 1.2) 170 (13 – Inf)
Vermont 13 (0 – 24) Likely decreasing 0.6 (0.2 – 0.9) -4.7 (29 – Inf)
Virginia 439 (371 – 494) Likely increasing 1.1 (0.9 – 1.2) 98 (22 – Inf)
Washington 221 (173 – 262) Decreasing 0.8 (0.6 – 0.9) -12 (Inf – Inf)
West Virginia 35 (15 – 52) Unsure 1 (0.6 – 1.3) -23 (11 – Inf)
Wisconsin 150 (115 – 187) Unsure 1 (0.8 – 1.2) -290 (17 – Inf)

“2019 Novel Coronavirus Covid-19 (2019-nCoV) Data Repository.” 2020. Johns Hopkins CSSE. https://github.com/CSSEGISandData/COVID-19.

Abbott, Sam, Joel Hellewell, James D. Munday, and Sebastian Funk. 2020. “NCoVUtils: Utility Functions for the 2019-Ncov Outbreak.” - - (-): –. https://doi.org/10.5281/zenodo.3635417.

Xu, Bo, Bernardo Gutierrez, Sarah Hill, Samuel Scarpino, Alyssa Loskill, Jessie Wu, Kara Sewalk, et al. n.d. “Epidemiological Data from the nCoV-2019 Outbreak: Early Descriptions from Publicly Available Data.” http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/337.